基于token的故障预测方法的实证研究

Ishleen Kaur, Neha Bajpai
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引用次数: 0

摘要

由于详尽的测试是不可能的,对易出错模块的预测可以用于对软件系统的组件进行优先级排序。人们提出了各种方法来预测易发故障模块。他们中的大多数使用模块度量作为质量评估器。在这项研究中,我们提出了一种基于标记的方法,并将我们的方法评估的度量与模块度量相结合,以进一步改善预测结果。我们在一个开源项目上进行了实验,以评估该方法。并将该方法与现有的易故障滤波技术进行了比较。结果表明,该方法是对易故障滤波技术的一种改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Empirical Study on Fault Prediction using Token-Based Approach
Since exhaustive testing is not possible, prediction of fault prone modules can be used for prioritizing the components of a software system. Various approaches have been proposed for the prediction of fault prone modules. Most of them uses module metrics as quality estimators. In this study, we proposed a tokenbased approach and combine the metric evaluated from our approach with the module metrics to further improve the prediction results. We conducted the experiment on an open source project for evaluating the approach. The proposed approach is further compared with the existing fault prone filtering technique. The results show that the proposed approach is an improvement over fault prone filtering technique.
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